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On some clustering approaches for graphs
Universitat Rovira i Virgili, Tarragona, Spain.ORCID iD: 0000-0002-5040-2089
Universitat Autònoma de Barcelona (UAB), Spain.ORCID iD: 0000-0002-0368-8037
2011 (English)In: Fuzzy Systems (FUZZ), 2011, IEEE conference proceedings, 2011, p. 409-415Conference paper, Published paper (Refereed)
Abstract [en]

In this paper we discuss some tools for graph perturbation with applications to data privacy. We present and analyse two different approaches. One is based on matrix decomposition and the other on graph partitioning. We discuss these methods and show that they belong to two traditions in data protection: noise addition/microaggregation and k-anonymity.

Place, publisher, year, edition, pages
IEEE conference proceedings, 2011. p. 409-415
Series
IEEE International Conference on Fuzzy Systems. Proceedings, ISSN 1098-7584
Keyword [en]
Data privacy, clustering, graph, k-anonymity, microaggregation
National Category
Information Systems Computer Sciences Discrete Mathematics
Identifiers
URN: urn:nbn:se:his:diva-10681DOI: 10.1109/FUZZY.2011.6007447ISI: 000295224300058Scopus ID: 2-s2.0-80053058551ISBN: 978-1-4244-7315-1 ISBN: 978-1-4244-7316-8 ISBN: 978-1-4244-7317-5 OAI: oai:DiVA.org:his-10681DiVA, id: diva2:833310
Conference
IEEE International Conference on Fuzzy Systems (FUZZ-IEEE 2011), 27-30 June 2011, Taipei, Taiwan
Available from: 2013-04-25 Created: 2015-02-12 Last updated: 2018-01-11Bibliographically approved

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Stokes, KlaraTorra, Vicenç

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CiteExportLink to record
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Citation style
  • apa
  • harvard1
  • ieee
  • modern-language-association-8th-edition
  • vancouver
  • Other style
More styles
Language
  • de-DE
  • en-GB
  • en-US
  • fi-FI
  • nn-NO
  • nn-NB
  • sv-SE
  • Other locale
More languages
Output format
  • html
  • text
  • asciidoc
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